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Do attitudes toward risk taking affect entrepreneurship? Evidence from second-generation Americans

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Abstract

This paper empirically investigates the impact of willingness to take risks on entrepreneurship. We use a quarter century of data on second-generation Americans from Current Population Surveys in conjunction with a measure of willingness to take risks based on the Global Preference Survey. The level of risk taking in the country of origin is found to have a positive and significant impact on the likelihood of being an entrepreneur. A one-standard deviation increase in risk taking increases the probability of being an entrepreneur by 18%. We find that risk taking is also robust to other preference and cultural factors such as trust, patience, and individualism, as well as several deep-root determinants of development.

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Notes

  1. Further, the Generalized Preference Survey was conducted in respective countries during 2012, while our sample consists of second generation population who were born, decades earlier in the US. Thus despite being nationally representative, the survey averages will naturally reflect contemporary demographic characteristics. Employing a demography adjusted measure of risk-taking in the country of origin also helps mitigate this concern.

  2. Dohmen et al., (2011a) provides evidence that risk attitudes persist between generations. We do not directly measure risk attitudes of individuals in the sample.

  3. Falk et al. (2018) show that the GPS measure of patience is not only strongly correlated with per capita income and other aggregate outcomes, but also dominates other preference measures in this respect.

  4. This is in contrast to some of the research that shows risk tolerance can change dramatically due to individual experiences (Jakiela and Ozier 2019) or beliefs and values, more generally, might converge towards those of the host country (Giavazzi et al., 2019).

  5. For a comprehensive discussion of the various economic theories of entrepreneurship, we refer the reader to Parker (2018).

  6. Dohmen et al. (2011a) document the transmission of attitudes towards risk and trust between generations, but indicate that regional variations can also affect these attitudes.

  7. Hsieh et al. (2017) argue that the inconclusive evidence of risk on entrepreneurship may reflect the likelihood of risk averse individuals compensating by investing in “balanced skills”, and in the process might even be more entrepreneurial.

  8. This is a repeated cross-section as individuals are not interviewed over the years. The sample period begins in 1995 because the CPS underwent a substantial change in 1994. Additionally, data on birthplace and parents’ birthplace are not available for years prior to 1994. The Bureau of Labor Statistics has also conducted the American Community Surveys annually since 2001. However, these surveys do not have information about the birthplace of parents.

  9. The General Social Survey (GSS) is another US based survey that contains data on various topics (such as demography, work, civil liberties, crime and violence, social mobility, etc.) since 1972. The survey includes information about the birth places of the ancestors of second or higher generation Americans. However, for our purpose, the GSS is not as comprehensive and consistent as the CPS-ASEC surveys. For example, the number of observations in each year is substantially smaller than that in the CPS. In addition, the number of country-of-origin is around 40, and most of them are European countries.

  10. As with the second generation sample, we only consider immigrants with parents from the same foreign country.

  11. We discuss this further in the next section and online appendix Table A.1.

  12. We are grateful to a referee for drawing this to our attention. In practice, the estimation results are almost identical. Our strategy is similar in spirit to Fairlie and Meyer (2003).

  13. We also estimated equation (1) by imposing \(\beta \) to be the same across all countries. In this case, it turns out that the correlation between estimated fixed effects \(\hat{R}_c\) and the average value of risk taking from the GPS is 0.97. Thus, results based on the latter approach are similar to those using the un-adjusted average risk value from the GPS that we report later in an online appendix table.

  14. Unless mentioned otherwise, for the rest of the paper, when we refer to risk taking, it will imply the adjusted value. We will continue to refer to the un-adjusted country level values available from Falk et al. (2018, 2016) as the average level of risk taking .

  15. The CPS data provides additional information about individuals’ work, including part-time/full-time status, number of weeks (un)employed, industry worked, etc. We do not include these variable into Eq. (2), because they pose a reverse-causality problem. For example, an individual may choose to work in an industry because of high entrepreneurial activity there. Further, some industries, might for various reasons tend to have a larger share of entrepreneurs than others leading to a problem of over-controlling. However, in robustness tests, we show that our results are not too sensitive to including these variables.

  16. We should note that the set here is less extensive compared to that of Falk et al. (2018), who also include temperature, precipitation and fraction of land area in tropics. Adding more geography controls has little effect on the risk-taking coefficient.

  17. Educational attainment may be influenced by the level of risk taking in the country-of-origin. However, excluding educational categories from our regressions does not have a substantial impact on the result.

  18. We should note that this strategy is vulnerable to Robinson’s (1950) ecological fallacy.

  19. See Fairlie and Lofstrom (2015), Kerr and Kerr (2020) for more on immigrant entrepreneurs.

  20. We also repeated these exercises while restricting the definition of entrepreneurship to the incorporated self-employed. Corresponding results are provided in Tables A.4 and A.6 in the online appendix.

  21. In many countries, legal traditions were typically introduced through conquest and colonization, and thus can be considered largely exogenous. However, La Porta et al. (2008) also observe that several countries adopted their laws voluntarily. For example, while Japan adopted the German legal system, Turkey and several Latin American countries adopted the French legal system voluntarily. The decision to adopt a certain legal system is likely to be driven a number of factors such as religious or political ideology, culture, or even preferences (including attitudes towards risk). In these cases, the relationship may not be truly exogenous, and legal origins itself proxies other deeper determinants.

  22. These are the same variables used in Table 1 of Galor and Özak (2016). We also considered the expanded set used in Table 2 of their paper, which differentiates between pre-1500 and post-1500 measures. This does not affect our results.

  23. The fact that risk-taking is insignificant is not a consequence of the reduced sample size. In the absence of the farming labor intensity variable, risk taking is significant.

  24. Rieger et al. (2015) conduct an international survey on risk preferences using about 7,000 individuals in 53 countries, and relate them to economic and cultural factors. They derive risk preferences from the participants’ willingness to pay for hypothetical lotteries, and distinguish risk attitudes in the gain and loss domain. Using the median relative risk premium (RRP) for gains and losses at the country level in their survey, we estimated the impact of these measures on entrepreneurship. However, given our set of controls, we can only use 35 countries. Nevertheless, the estimates have the correct sign and, in the case of the RRP for gains, a large coefficient. However, they are not statistically significant. One drawback is that the survey is not as representative and extensive as the GPS. The participants were first- or second-year undergraduate students from departments of economics, finance, or business administration.

  25. The Hofstede cultural dimensions are widely used in economics and management. However, they are based mainly on IBM employees, and thus, despite their popularity, are not necessarily representative samples for the countries surveyed.

  26. Their sample is second generation Americans in the Generalized Social Survey.

  27. As with the measure of risk, we construct a demography adjusted measure of trust.

  28. In studies that preceded theirs, the more commonly used measure of trust is a question in the World Values Survey and the GSS (for USA) asking “Generally speaking, would you say that most people can be trusted or that you need to be very careful in dealing with people?” Falk et al. (2018) note that this value is strongly correlated (0.49) with the GPS measure, but is also not robust in a horse race with their measure of patience in cross-country regressions.

  29. We use these terms interchangeably. See Galor and Özak (2016) for an extensive discussion and the related literature, including evidence on inter-generational transmission.

  30. As with risk taking and trust, we use the demography adjusted measure.

  31. LTO “...stands for a society which fosters virtues oriented towards future rewards, in particular adaptation, perseverance and thrift. Short Term orientation stands for a society which fosters virtues related to the past and present, in particular respect for tradition, preservation of “face”, and fulfilling social obligations” (Hofstede et al., 2010). We normalize the index dividing by 100 so that it has a range of 0 to 1. Lower values reflect short-term orientation while higher values reflect long-term orientation. It is interesting that in the definition, while long-term orientation seems to capture thrift, short-term orientation is equated with traditional values, which at least in our view, is not the opposite. We should clarify that unlike the other cultural dimensions which are based on interviews of IBM employees, Hofstede et al construct LTO based on factor analysis of three questions from the World Values Survey. See Hofstede et al. (2010) for further details, and also a brief discussion in Figlio et al. (2019, p 280). As a result the sample of countries is larger for LTO than for the other Hofstede measures. Unlike the GPS measures, we do not adjust for demographics as the distribution of the underlying sample is not available to us.

  32. Pan et al. (2019) suggest that UAI reflects Knightian uncertainty. They use historical ship arrival records from 1820 to 1957 to assign last names to ethnicity. After identifying the national cultural heritage of US CEO’s, they find a more uncertainty-averse (high UAI) cultural heritage is significantly less likely to engage in corporate acquisitions.

  33. For columns 6, 8, and 10, risk-taking remains significant even when long-term orientation/individualism/uncertainty avoidance are dropped, i.e. the results are not specific to the fewer countries in these regressions.

  34. As with the tables in the main text, we use the demography adjusted patience and trust variables. When we used their un-adjusted counterparts in earlier versions of this study, the variables were even less significant. The results are available upon request.

  35. We repeated our baseline regression for these smaller sample sizes. Risk taking remained significant.

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  1. Department of Economics, Louisiana State University, Baton Rouge, LA, 70803, USA

    Areendam Chanda & Bulent Unel

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We are grateful to Oded Galor and three anonymous referees for their thoughtful comments and suggestions. We also thank James Ang and Benjamin Enke for sharing data, and Elias Dinopoulos, Rob Fairlie, Carter Hill, Daniel Keniston, Robert Newman, Barton Willage, Qiankun Zhou, and seminar participants at Louisiana State University, LSU-Tulane conference, and the 2020 Annual Southern Economic Association meetings, for valuable feedback.

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Chanda, A., Unel, B. Do attitudes toward risk taking affect entrepreneurship? Evidence from second-generation Americans. J Econ Growth 26, 385–413 (2021). https://doi.org/10.1007/s10887-021-09197-8

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